With the same idea of 2-1, using quick sort and insertion sort answer the following questions

(explain this to the best of your ability)

2-1 Insertion sort on small arrays in merge sort Although merge sort runs in (n lgn) worst-case time and insertion sort runs in (na) worst-case time, the constant factors in insertion sort can make it faster in practice for small problem sizes on many machines. Thus, it makes sense to coarsen the leaves of the recursion by using insertion sort within merge sort when subproblems become sufficiently small. Consider a modification to merge sort in which n/k sublists of length k are sorted using insertion sort and then merged using the standard merging mechanism, where k is a value to be determined. b) Find and fully understand the codes of quicksort and insertion sort. Say "Yes" if you do. 2-1 Insertion sort on small arrays in merge sort Although merge sort runs in (n lgn) worst-case time and insertion sort runs in (na) worst-case time, the constant factors in insertion sort can make it faster in practice for small problem sizes on many machines. Thus, it makes sense to coarsen the leaves of the recursion by using insertion sort within merge sort when subproblems become sufficiently small. Consider a modification to merge sort in which n/k sublists of length k are sorted using insertion sort and then merged using the standard merging mechanism, where k is a value to be determined. b) Find and fully understand the codes of quicksort and insertion sort. Say "Yes" if you do